Differential Susceptibility of Allogeneic Targets to Indirect CD4 Immunity Generates Split Tolerance
Bibliographic record
Abstract
CD4 T cells frequently help to activate CD8 T and B cells that effect transplant rejection. However, CD4 T cells alone can reject transplants, either directly or indirectly. The relative effectiveness of indirect CD4 immunity in rejecting different types of allogeneic grafts is unknown. To address this, we used a TCR transgenic mouse model in which indirect CD4 alloimmunity alone can be studied. We challenged transgenic recipients with hematopoietic cells and shortly thereafter skin transplants that could only be rejected indirectly, and observed Ag-specific indirect donor B cell and skin rejection, but not T cell elimination, reflecting a state of split tolerance. Deficiency of indirect CD4 alloimmunity in donor T cell rejection was also apparent when acute indirect rejection of donor islets occurred despite generation and maintenance of mixed T cell chimerism, due to migration of the few passenger T cells into recipient circulation. Although passenger lymphocytes delayed indirect islet rejection, they enhanced rejection by a full repertoire capable of both direct and indirect reactivity. Interestingly, the persistence of chimerism was associated with the eventual development of tolerance, as demonstrated by acceptance of donor skin grafts given late to hematopoietic cell recipients, and hyporesponsiveness of transgenic T cells from islet recipients in vitro. Mechanistically, tolerance was recessive and associated with progressive down-regulation of CD4. Collectively, our data indicate that indirect CD4 immunity is not equally destructive toward different types of allogeneic grafts, the deficiency of which generates split tolerance. The futility of these responses can convert immunity into tolerance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".